Titlebook: Machine Learning Challenges; Evaluating Predictiv Joaquin Qui?onero-Candela,Ido Dagan,Florence d’Alc Conference proceedings 2006 Springer-V

吹牛需要藝術(shù)

Lessons Learned in the Challenge: Making Predictions and Scoring Them,lems in local scoring rules such as the negative logarithm of predictive density (NLPD), and illustrate with examples that many of these problems can be avoided by a distance-sensitive rule such as the continuous ranked probability score (CRPS).

外貌

Estimating Predictive Variances with Kernel Ridge Regression,eave-one-out cross-validation is shown to eliminate the bias inherent in estimates of the predictive variance. Results obtained on all three regression tasks comprising the predictive uncertainty challenge demonstrate the value of this approach.

臭了生氣

Textual Entailment Recognition Using Inversion Transduction Grammars, for the RTE problem that employ simple generic Bracketing ITGs. Experimental results show that, even in the absence of any thesaurus to accommodate lexical variation between the Text and the Hypothesis strings, surprisingly strong results for a number of the task subsets are obtainable from the Bracketing ITG’s structure matching bias alone.

originality

DOLT

Using Bleu-like Algorithms for the Automatic Recognition of Entailment, 50%. Moreover, in this paper we explore the application of .-like algorithms, finding that they can reach an accuracy of around 56%, which proves its possible use as a baseline for the task of recognizing entailment.

Alcove

Combining Lexical Resources with Tree Edit Distance for Recognizing Textual Entailment,xtual entailment: WordNet and a word-similarity database. In both cases we derive entailment rules that are used by the Tree Edit Distance Algorithm. We carried out a number of experiments over the PASCAL-RTE dataset in order to estimate the contribution of different combinations of the available resources.

爆米花

subacute

DUCE

PTCA635

es selbstbestimmten Lernens er?ffnet Pythagoras 360° eine hohe Individualisierung des Lernprozesses. Abschlie?end werden geplante Weiterentwicklungen wie die Einbindung verschiedener Muskelskelette und eine m?gliche Implementierung des Systems in das Lehramtscurriculum skizziert.